System for Mapping Traffic Lights and Associated Traffic Light Cycle Times

1. A system for mapping traffic lights and associated traffic light cycle times for use in autonomous vehicle navigation, the system comprising at least one processor programmed to: receive, from a first vehicle, at least one location identifier associated with a traffic light detected along a road segment; receive, from the first vehicle, at least one indicator of traffic light state timing associated with the detected traffic light, wherein the at least one indicator of traffic light state timing is determined based on analysis of at least one image captured from an environment of the first vehicle, the analysis including application of at least one of a trained system or a computer vision algorithm; update an autonomous vehicle road navigation model relative to the road segment, wherein the update is based on the at least one location identifier and based on the at least one indicator of traffic light state timing associated with the traffic light detected along the road segment; and distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles, wherein: the at least one processor is further programmed to determine whether the detected traffic light is sensor-operated, the determination of whether the detected traffic light is sensor-operated is based on the at least one indicator of traffic light state timing and based on navigational information, received from the first vehicle, indicative of one or more aspects of motion of the first vehicle along the road segment, and the determination of whether the detected traffic light is sensor-operated is based on information received from the first vehicle indicating a detection of a sensor structure associated with a road surface in a vicinity of the detected traffic light.

2. The system of claim 1, wherein the autonomous vehicle road navigation model includes a mapped location of the detected traffic light, and wherein the at least one location identifier received from the first vehicle is used to update the mapped location of the detected traffic light.

3. The system of claim 2, wherein the mapped location corresponds to a location in real-world coordinates.

4. The system of claim 1, wherein the update to the autonomous vehicle road navigation model includes an indication of at least one of: an amount of time the detected traffic light is expected to remain in at least a first state; or an amount of time until when the traffic light is expected to turn from the first state to a second state.

5. The system of claim 4, wherein the first state includes one of a green light state, a yellow light state, or a red light state.

6. The system of claim 4, wherein the update to the autonomous vehicle road navigation model includes an indication of an amount of time the detected traffic light is expected to remain in a second state.

7. The system of claim 4, wherein the update to the autonomous vehicle road navigation model includes an indication of an amount of time the detected traffic light is expected to remain in a third state.

8. The system of claim 1, wherein the first vehicle is configured to detect a first traffic light state transition and a second traffic light state transition.

9. The system of claim 8, wherein the first traffic light state transition includes a transition from a yellow light state to a red light state, and wherein the second traffic light state transition includes a transition from a red light state to a green light state.

10. The system of claim 8, wherein the first traffic light state transition includes a transition from a red light state to a green light state, and wherein the second traffic light state transition includes a transition from a green light state to a yellow light state.

11. The system of claim 1, wherein the indicator of traffic light state timing includes one or more time values each associated with a corresponding observed traffic light state change event for the detected traffic light.

12. The system of claim 1, wherein the sensor structure includes tar lines on the road surface in a pattern associated with the sensor structure.

13. The system of claim 1, wherein the at least one processor is further programmed to: receive from the first vehicle a first time of day associated with detection of the traffic light by a system of the first vehicle; receive from a second vehicle a second time of day associated with detection of the traffic light by a system of the second vehicle; receive from the second vehicle at least one additional indicator of traffic light state timing associated with the detected traffic light; and determine, based at least on the first time of day, the second time of day, the at least one indicator of traffic light state timing, and the at least one additional indicator of traffic light state timing, whether the traffic light state timing of the detected traffic light varies with respect to time of day.

14. The system of claim 1, wherein the at least one processor is further programmed to: receive, from a second vehicle, at least one location identifier associated with the traffic light detected along a road segment; receive, from the second vehicle, at least one indicator of traffic light state timing associated with the detected traffic light; and update the autonomous vehicle road navigation model relative to the road segment, wherein the update is based on the at least one location identifier received from the second vehicle and based on the at least one indicator of traffic light state timing received from the second vehicle.

15. The system of claim 1, wherein the updated autonomous vehicle road navigation model is distributed to vehicles among the plurality of autonomous vehicles approaching the traffic light first and then to various other vehicles among the plurality of autonomous vehicles.

16. The system of claim 1, wherein the updated autonomous vehicle road navigation model is distributed to vehicles among the plurality of autonomous vehicles navigating the road segment.

17. A method for mapping traffic lights and associated traffic light cycle times for use in autonomous vehicle navigation, the method comprising: receiving, from a first vehicle, at least one location identifier associated with a traffic light detected along a road segment; receiving, from the first vehicle, at least one indicator of traffic light state timing associated with the detected traffic light, wherein the at least one indicator of traffic light state timing is determined based on analysis of at least one image captured from an environment of the first vehicle, the analysis including application of at least one of a trained system or a computer vision algorithm; updating an autonomous vehicle road navigation model relative to the road segment, wherein the update is based on the at least one location identifier and based on the at least one indicator of traffic light state timing associated with the traffic light detected along the road segment; and distributing the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles, wherein: the method further comprises determining whether the detected traffic light is sensor-operated; and the determination of whether the detected traffic light is sensor-operated is based on: the at least one indicator of traffic light state timing, navigational information, received from the first vehicle, indicative of one or more aspects of motion of the first vehicle along the road segment, and information received from the first vehicle indicating a detection of a sensor structure associated with a road surface in a vicinity of the detected traffic light.

18. The method of claim 17, wherein the autonomous vehicle road navigation model includes a mapped location of the detected traffic light, and wherein the at least one location identifier received from the first vehicle is used to update the mapped location of the detected traffic light.

19. The method of claim 17, wherein the update to the autonomous vehicle road navigation model includes an indication of at least one of: an amount of time the detected traffic light is expected to remain in at least a first state; or an amount of time until when the traffic light is expected to turn from the first state to a second state.

20. The method of claim 19, wherein the first state includes one of a green light state, a yellow light state, or a red light state.

21. The method of claim 19, wherein the update to the autonomous vehicle road navigation model includes an indication of an amount of time the detected traffic light is expected to remain in a second state.

22. The method of claim 17, wherein the first vehicle is configured to detect a first traffic light state transition and a second traffic light state transition.

23. The method of claim 22, wherein the first traffic light state transition includes a transition from a yellow light state to a red light state, and wherein the second traffic light state transition includes a transition from a red light state to a green light state.

24. The method of claim 22, wherein the first traffic light state transition includes a transition from a red light state to a green light state, and wherein the second traffic light state transition includes a transition from a green light state to a yellow light state.

25. The method of claim 17, wherein the indicator of traffic light state timing includes one or more time values each associated with a corresponding observed traffic light state change event for the detected traffic light.

26. The method of claim 17, wherein the updated autonomous vehicle road navigation model is distributed to vehicles among the plurality of autonomous vehicles navigating the road segment.